文章基本信息

标题：SENTIMENT CLASSIFICATION OF MOVIE REVIEWS BY SUPERVISED MACHINE LEARNING APPROACHES
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作者：P.KALAIVANI ; Dr. K.L.SHUNMUGANATHAN
期刊名称：Indian Journal of Computer Science and Engineering
印刷版ISSN：2231-3850
电子版ISSN：0976-5166
出版年度：2013
卷号：4
期号：4
页码：285-292
出版社：Engg Journals Publications
摘要：Large volumes of data are available in the web. The discussion forum, review sites, blogs and news corpora are some of the opinion rich resources. The opinions obtained from those can be classified and used for gathering online customer�s preferences. Techniques are being applied to design a system that identifies and classify opinions spread largely in the internet. Few different problems such as sentiment classification, feature based classification and handling negotiations are predominating this research community. This paper studies online movie reviews using sentiment analysising approaches. In this study, sentiment classification techniques were applied to movie reviews. Specifically, we compared three supervised machine learning approaches SVM, Navie Bayes and kNN for Sentiment Classification of Reviews. Empirical results states that SVM approach outperformed the Navie Bayes and kNN approaches, and the training dataset had a large number of reviews, SVM approach reached accuracies of atleast 80%.
关键词：opinions; sentiment classification; online reviews; supervised machine learning algorithm.